Start from the governing relation
This is the smallest equation that preserves the physics needed for the formula.
FORMULA / 015
Interactive derivation module for DCT and JPEG compression.
Problem Definition
A JPEG image keeps smooth regions compact but may create block artifacts near sharp edges.
| Symbol | Quantity | Unit | Meaning |
|---|---|---|---|
| $C_{u,v}$ | DCT coefficient | 依資料而定 | Strength of one cosine basis. |
| $Q_{u,v}$ | Quantization step | 依資料而定 | Loss control per frequency. |
| $8\times8$ | JPEG block | pixels | Local transform size. |
Analytical Derivation
| Item | Assumption |
|---|---|
| Assumption 1 | Linear time-invariant or locally linear behavior is assumed when using transfer functions. |
| Assumption 2 | Parameters are treated as constant over the analysis interval. |
| Assumption 3 | Numerical plots are educational approximations, not full circuit or field solvers. |
This is the smallest equation that preserves the physics needed for the formula.
The model is simplified so the dominant mechanism is visible.
The final form is the one used for design, simulation, or measurement review.
parameter $\to0$dominant term remainsThe formula reduces to its simplest physical behavior.
parameter $\to\infty$parasitics and implementation limits dominateThe closed-form equation becomes a warning rather than a full implementation model.
Parametric Verification
Use the sliders to change the physical parameters and watch the formula expose its behavior. The metric panel keeps sample count and compute latency visible so the visualization remains an engineering instrument, not only a picture.
INTERACTIVE MODULE
Engineering Application
import numpy as np
def quantize_dct(c, q):
return np.round(c / q).astype(int)